Instructions to use ByteDance/ID-Patch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ByteDance/ID-Patch with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ByteDance/ID-Patch", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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- **Paper:** https://arxiv.org/abs/2411.13632
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## License
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The model is released under [CreativeML Open RAIL++-M License](https://huggingface.co/ByteDance/ID-Patch/blob/main/LICENSE)
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- **Paper:** https://arxiv.org/abs/2411.13632
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## License
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The model is released under [CreativeML Open RAIL++-M License](https://huggingface.co/ByteDance/ID-Patch/blob/main/LICENSE.md)
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